Titlebook: Intelligent Data Engineering and Automated Learning – IDEAL 2020; 21st International C Cesar Analide,Paulo Novais,Hujun Yin Conference proc

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书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2020影响因子(影响力)




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2020影响因子(影响力)学科排名




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书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2020网络公开度学科排名




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2020被引频次




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2020被引频次学科排名




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2020年度引用




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2020年度引用学科排名




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2020读者反馈




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2020读者反馈学科排名

缩影

Data Pre-processing and Data Generation in the Student Flow Case Studyon Ministry. DGEEC maintains those outcomes for each school year, therefore, this study seeks a longitudinal view based on student flow. The document reports the data pre-processing, a stochastic model based on the pre-processed data and a data generation process that uses the previous model.

Omnipotent

盘旋

Deep Learning in Aeronautics: Air Traffic Trajectory Classification Based on Weather Reportside, we created a model based on a multi-layer perceptron capable of determining the approach trajectory of an aircraft thirty minutes prior to the expected landing time. Experiments on aircraft trajectories from Toulouse to Seville, show an accuracy, recall and F1-score higher than 0.9 for the resultant predictive model.

maladorit

Stabilization of Dataset Matrix Form for Classification Dataset Generation and Algorithm Selectioncation dataset aiming to break the symmetry. We experimented with it in the meta-learning problems of datasets generation and algorithm selection which were solved by conditional generative adversarial nets with convolutional networks.

Foment

Unified Performance Measure for Binary Classification Problemsmbalanced classification problems. . is compared with alternative performance measures, like the .-score or Accuracy, in both simulated confusion matrices and real datasets. The proposed measure outperforms the alternatives, providing a promising new research line.

使坚硬

净礼

0302-9743 ning, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. ..*. The conference was held virtually due to the COVID-19 pandemic..978-3-030-62364-7978-3-030-62365-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

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A Preprocessing Approach for Class-Imbalanced Data Using SMOTE and Belief Function Theoryheory are then enforced to detect and remove generated instances that are in noisy and overlapping regions. Experiments on noisy artificial datasets show that our proposal significantly outperforms other popular oversampling methods.

farewell